Data about the death penalty in the United States as of January 7, 2022, from the non-profit organization Death Penalty Information Center.
state: state name (including District of Columbia)region: US Census regiondivision: US Census regional subdivisioncourt: US Court of Appeals regional circuitdp1: whether or not the state legally has the death penalty (yes/no)dp2: dp1 but also indicates states that have a governor’s moratoriumabolished: year capital punishment was legally abolished in the statepost1976: number of executions after 1976 (state only)pre1976: number of executions before 1976 (may include federal/military)prisoners: total number of prisoners currently on death rowwomen: number of women on death row (subset of prisoners)freed: number of innocent people later freed from death rowclemency: number of people who were granted clemencylife: whether the state can sentence an adult to life without parolelifejuvie: whether the state can sentence a juvenile to life without parolefelony: whether someone can get the death penalty as a felony accessorysentence: who decides on whether someone gets a death penalty sentenceRows: 51
Columns: 17
$ state <chr> "Alabama", "Alaska", "Arizona", "Arkansas", "California", "C…
$ region <chr> "South", "West", "West", "South", "West", "West", "Northeast…
$ division <chr> "East Southern Central", "Pacific", "Mountain", "West Southe…
$ court <chr> "Eleventh", "Ninth", "Ninth", "Eighth", "Ninth", "Tenth", "S…
$ dp1 <chr> "yes", "no", "yes", "yes", "yes", "no", "no", "no", "no", "y…
$ dp2 <chr> "yes", "no", "yes", "yes", "yes, in moratorium", "no", "no",…
$ abolished <dbl> NA, 1957, NA, NA, NA, 2020, 2015, 2016, 1981, NA, NA, 1957, …
$ post1976 <dbl> 68, 0, 37, 31, 13, 1, 1, 16, 0, 99, 76, 0, 3, 12, 20, 0, 0, …
$ pre1976 <dbl> 708, 12, 104, 478, 725, 101, 126, 24, 118, 347, 950, 49, 26,…
$ prisoners <dbl> 171, NA, 118, 31, 699, NA, NA, NA, NA, 338, 45, NA, 8, NA, 8…
$ women <dbl> 5, NA, 3, 0, 22, NA, NA, NA, NA, 3, 1, NA, 1, NA, 0, NA, 0, …
$ freed <dbl> 7, 0, 10, 1, 5, 0, 0, 1, 0, 30, 7, 0, 1, 21, 2, 0, 0, 1, 11,…
$ clemency <dbl> 1, 0, 0, 2, 0, 3, 0, 1, 3, 6, 9, 0, 1, 188, 3, 0, 0, 4, 2, 0…
$ life <chr> "yes", "no", "yes", "yes", "yes", "yes", "yes", "yes", "yes"…
$ lifejuvie <chr> "yes", "no", "yes", "no", "no", "yes", "no", "no", "no", "ye…
$ felony <chr> "no", NA, "yes", "yes", "yes", NA, NA, NA, NA, "yes", "no", …
$ sentence <chr> "jury + judge", NA, "jury", "jury", "jury", NA, NA, NA, NA, …
# A tibble: 6 × 17
state region division court dp1 dp2 abolished post1976 pre1976 prisoners
<chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 Alaba… South East Sou… Elev… yes yes NA 68 708 171
2 Alaska West Pacific Ninth no no 1957 0 12 NA
3 Arizo… West Mountain Ninth yes yes NA 37 104 118
4 Arkan… South West Sou… Eigh… yes yes NA 31 478 31
5 Calif… West Pacific Ninth yes yes,… NA 13 725 699
6 Color… West Mountain Tenth no no 2020 1 101 NA
# … with 7 more variables: women <dbl>, freed <dbl>, clemency <dbl>,
# life <chr>, lifejuvie <chr>, felony <chr>, sentence <chr>
year: year (includes each year from 1968 to 2021)total: total prisoners on death row during that yearRows: 53
Columns: 2
$ year <dbl> 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 1977, 1978…
$ total <dbl> 517, 575, 631, 642, 334, 134, 244, 488, 420, 423, 482, 539, 691,…
# A tibble: 6 × 2
year total
<dbl> <dbl>
1 1968 517
2 1969 575
3 1970 631
4 1971 642
5 1972 334
6 1973 134
state: state name (including District of Columbia and Federal Government)yxxxx: year (includes each year from 1976 to 2021)Rows: 52
Columns: 46
$ state <chr> "Alabama", "Alaska", "Arizona", "Arkansas", "California", "Color…
$ y2021 <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2020 <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2019 <dbl> 3, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2018 <dbl> 2, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2017 <dbl> 3, 0, 0, 4, 0, 0, 0, 0, 0, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2016 <dbl> 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2015 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2014 <dbl> 0, 0, 1, 0, 0, 0, 0, 0, 0, 8, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2013 <dbl> 1, 0, 2, 0, 0, 0, 0, 0, 0, 7, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2012 <dbl> 0, 0, 6, 0, 0, 0, 0, 1, 0, 3, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2011 <dbl> 6, 0, 4, 0, 0, 0, 0, 1, 0, 2, 4, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y2010 <dbl> 5, 0, 1, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y2009 <dbl> 6, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0…
$ y2008 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0…
$ y2007 <dbl> 3, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0…
$ y2006 <dbl> 1, 0, 0, 0, 1, 0, 0, 0, 0, 4, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0…
$ y2005 <dbl> 4, 0, 0, 1, 2, 0, 1, 1, 0, 1, 3, 0, 0, 0, 5, 0, 0, 0, 0, 0, 1, 0…
$ y2004 <dbl> 2, 0, 0, 1, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0…
$ y2003 <dbl> 3, 0, 0, 1, 0, 0, 0, 0, 0, 3, 3, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0…
$ y2002 <dbl> 2, 0, 0, 0, 1, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y2001 <dbl> 0, 0, 0, 1, 1, 0, 0, 2, 0, 1, 4, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0…
$ y2000 <dbl> 4, 0, 3, 2, 1, 0, 0, 1, 0, 6, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1999 <dbl> 2, 0, 7, 4, 2, 0, 0, 2, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0…
$ y1998 <dbl> 1, 0, 4, 1, 1, 0, 0, 0, 0, 4, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0…
$ y1997 <dbl> 3, 0, 2, 4, 0, 1, 0, 0, 0, 1, 0, 0, 0, 2, 1, 0, 0, 1, 1, 0, 1, 0…
$ y1996 <dbl> 1, 0, 2, 1, 2, 0, 0, 3, 0, 2, 2, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0…
$ y1995 <dbl> 2, 0, 1, 2, 0, 0, 0, 1, 0, 3, 2, 0, 0, 5, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1994 <dbl> 0, 0, 0, 5, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 0…
$ y1993 <dbl> 0, 0, 2, 0, 1, 0, 0, 2, 0, 3, 2, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1992 <dbl> 2, 0, 1, 2, 1, 0, 0, 1, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1991 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1990 <dbl> 1, 0, 0, 2, 0, 0, 0, 0, 0, 4, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1989 <dbl> 4, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1988 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0…
$ y1987 <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 5, 0, 0, 0, 0, 0, 0, 0, 8, 0, 0, 0…
$ y1986 <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1985 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0…
$ y1984 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 2, 0, 0, 0, 0, 0, 0, 0, 5, 0, 0, 0…
$ y1983 <dbl> 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0…
$ y1982 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1981 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0…
$ y1979 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1977 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ y1976 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0…
$ ...46 <dbl> 68, 0, 37, 31, 13, 1, 1, 16, 0, 99, 76, 0, 3, 12, 20, 0, 0, 3, 2…
# A tibble: 6 × 46
state y2021 y2020 y2019 y2018 y2017 y2016 y2015 y2014 y2013 y2012 y2011 y2010
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Alaba… 1 1 3 2 3 2 0 0 1 0 6 5
2 Alaska 0 0 0 0 0 0 0 0 0 0 0 0
3 Arizo… 0 0 0 0 0 0 0 1 2 6 4 1
4 Arkan… 0 0 0 0 4 0 0 0 0 0 0 0
5 Calif… 0 0 0 0 0 0 0 0 0 0 0 0
6 Color… 0 0 0 0 0 0 0 0 0 0 0 0
# … with 33 more variables: y2009 <dbl>, y2008 <dbl>, y2007 <dbl>, y2006 <dbl>,
# y2005 <dbl>, y2004 <dbl>, y2003 <dbl>, y2002 <dbl>, y2001 <dbl>,
# y2000 <dbl>, y1999 <dbl>, y1998 <dbl>, y1997 <dbl>, y1996 <dbl>,
# y1995 <dbl>, y1994 <dbl>, y1993 <dbl>, y1992 <dbl>, y1991 <dbl>,
# y1990 <dbl>, y1989 <dbl>, y1988 <dbl>, y1987 <dbl>, y1986 <dbl>,
# y1985 <dbl>, y1984 <dbl>, y1983 <dbl>, y1982 <dbl>, y1981 <dbl>,
# y1979 <dbl>, y1977 <dbl>, y1976 <dbl>, ...46 <dbl>
state: state name (including US Government and US Military)black: number of black death row inmateswhite: number of white death row inmates (non-latinx)latinx: number of latinx death row inmatesnativeam: number of native american death row inmatesasian: number of asian death row inmatesunknown: number of death row inmates with unknown race/ethnicityRows: 30
Columns: 7
$ state <chr> "Alabama", "Arizona", "Arkansas", "California", "Florida", "G…
$ black <dbl> 86, 18, 15, 250, 130, 23, 0, 2, 3, 3, 44, 22, 7, 0, 2, 24, 1,…
$ white <dbl> 83, 70, 15, 229, 187, 19, 8, 6, 6, 24, 18, 16, 14, 2, 4, 31, …
$ latinx <dbl> 2, 23, 1, 183, 19, 3, 0, 0, 0, 0, 3, 1, 0, 0, 6, 9, 0, 4, 3, …
$ nativeam <dbl> 0, 4, 0, 9, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 2, 1…
$ asian <dbl> 0, 3, 0, 28, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 2, 0, 1, 1, 0, …
$ unknown <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1…
# A tibble: 6 × 7
state black white latinx nativeam asian unknown
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Alabama 86 83 2 0 0 0
2 Arizona 18 70 23 4 3 0
3 Arkansas 15 15 1 0 0 0
4 California 250 229 183 9 28 0
5 Florida 130 187 19 1 1 0
6 Georgia 23 19 3 0 0 0